Project Summary (Abstract) Quantitation of regional myocardial blood flow (MBF) and coronary flow reserve (CFR) is not currently widely performed for diagnosis and management of coronary artery disease (CAD). The development of a widely available, accurate, inexpensive, quantitative noninvasive method for the measurement of MBF and CFR would provide a thorough assessment of the full extent of CAD and diffuse microvascular diseases. It would also pro- vide an early detection of the development of cardiac allograft vasculopathy (CAV) in orthotopic heart transplant (OHT) patients. Single photon emission computed tomography (SPECT), the most widely applied noninvasive method for the detection and risk stratification of CAD, is less costly for both operator and patients and more widely available than positron emission tomography (PET), the gold standard for the quantification of MBF and CFR. In our earlier work we developed methods to noninvasively quantify MBF and CFR with the acquisition of dynamic data on a conventional SPECT camera. This method demonstrated the capability of estimating MBF from widely used clinical imaging agents with marginal flow-extraction products. Our hypothesis is that dy- namic cardiac SPECT with conventional 99mTc-labeled agents provides quantitation of MBF and CFR which cannot be obtained by conventional static SPECT. This promises to improve the diagnosis and prognostic as- sessment of CAD, and permit early identification of the onset and progression of CAV in OHT patients. We propose a systematic study of quantitative myocardial perfusion imaging using a combined dynamic and static cardiac SPECT (DSC-SPECT) rest/stress protocol 1) to assess the extent of coronary involvement in patients with known and highly suspected CAD, and 2) to evaluate MBF and CFR as an early indicator of CAV. A unique aspect of this work is our ability to quantify MBF by estimating kinetic model parameters and the blood input function, directly from acquired projections using slow camera rotation speed without any need for arterial blood sampling. Our methods include corrections for cardiac motion due to cardiac deformation and respiration (6D dynamic modeling). Our study addresses the challenges related to the development of algorithms that convert dynamically acquired scintigraphic data to meaningful clinical information and optimizes the related clinical protocols. We believe that with the successful demonstration of dynamic SPECT in the proposed protocols, our methods will support a change of the current static SPECT myocardial perfusion imaging (MPI) protocols to dynamic SPECT MPI protocols with application of even standard dual-headed cameras.